Most power sources and loads are nonlinear systems and have an optimum operating point. The online identification of the optimum operating point and the development of a corresponding control system which enables the nonlinear system to robustly operate at such a point constitute an important challenge. In the design of these control systems that desirably maintain these corresponding nonlinear systems operating at or near their optimum operating point, power electronics circuits and systems have been implemented. Typically, power electronic circuits and systems manipulate energy flows of power sources and loads with switches. Consequently, switching power converters are also nonlinear large-signal systems.
Switching actions produce ripple, which cannot be avoided without a power loss penalty. In many power converters and their controls, ripple is at best a substitute for a switching control (as in hysteresis control) and at worst a nuisance and a source of noise and interference. Ripple has typically not been considered as a source of information, and numerous techniques have been configured to minimize ripple and discontinuities of switching by smoothing out the switch actions and averaging through filters.
However, ripple which is inherent to the switching actions and represents a consistent perturbation signal has been found to be a source of information and a basis for control. Research results have shown that significant control objectives, such as cost-function optimization, can be addressed with a ripple correlation technique. Ripple correlation control (RCC) has opened a whole suite of new possibilities for converter action and for control loops. Further, power electronics are uniquely suited for this approach because of their self-perturbed internal switching action.
RCC is a nonlinear control approach applicable to power electronic circuits, which makes use of voltage, current, or power ripple and correlates the ripple with switching functions to effect control, as disclosed in U.S. Pat. No. 5,801,519. RCC has been shown to directly support cost-function minimization and maximization, and can be applied, for example, to dynamic power optimization. RCC has also been applied to adaptive dead time adjustment, solar power processing, and motor power minimization. Typical applications have included active maximization of converter efficiency and other nonlinear functions.
Among these typical applications figure solar panels, which can deliver maximum power at a particular voltage and current point that varies with the temperature and illumination affecting the solar panels. Since 1968, researchers have been developing different maximum power point tracker (MPPT) methods to operate solar panels at their maximum operating points or levels. Energy processing for solar panels is generally done with modern power electronics, because switching power converters as designed for power electronics applications offer high efficiency and are readily controlled. Nearly all recent work on MPPT approaches involves power electronics to implement the solutions.
Tracking the maximum power point is extremely important for solar applications. While the price of solar panels has dropped dramatically over the past 30 years, solar panel size and cost are dominant factors in a solar installation. In the most basic installations, solar panels are connected directly to a battery through a diode, which forces the panels to operate at a voltage that follows the battery characteristics, not the panel characteristics, and does not deliver maximum power. More sophisticated applications use a switching power converter to interface between the solar panel and the load. When a switching power converter is present, RCC represents a minor addition to the converter control to achieve tracking of the panel maximum power with minimal extra cost. Moreover, while RCC is a general method for optimization method, its application to the solar MPPT problem is well established. For example, the power ripple is correlated with the voltage ripple to build an MPPT for a solar panel.
RCC has previously been cast as a continuous-time technique, implemented with analog circuits. In the analog environment, RCC was implemented by utilizing a continuous signal processing of the systems being controlled. However, the continuous-time technique of the RCC typically requires that the controller operates with a substantially high volume of information and a correspondingly high sampling rate, which may be problematic. Further, many applications can benefit from an RCC technique that provides reduced quiescent power and mode-switching.
Therefore, a need exists for a ripple correlation control that operates a switching power converter at optimum conditions with a low sampling rate that overcomes the problems noted above and others previously experienced for addressing issues of volume of information, reduced quiescent power or mode-switching. These and other needs will become apparent to those of skill in the art after reading the present specification.